Multiobjective Evolutionary Approach to Optimal Reservoir Operation

AbstractThis paper presents an application of the Multiobjective Differential Evolution (MoDE) algorithm for the optimal operation of a complex multipurpose reservoir system. The developed algorithm (MoDE) is compared with the Genetic Algorithm (NSGA-II) using a set of common test problems and the c...

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Bibliographic Details
Published in:Journal of computing in civil engineering 2013-03, Vol.27 (2), p.139-147
Main Authors: Schardong, Andre, Simonovic, Slobodan P, Vasan, A
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Buildings. Public works
Computation methods. Tables. Charts
Deviation
Distribution. Storage
Exact sciences and technology
Inflow
Minimization
Optimization
Reservoirs
Shortages
Structural analysis. Stresses
Technical Papers
Water quality
Water supply. Pipings. Water treatment
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Summary:AbstractThis paper presents an application of the Multiobjective Differential Evolution (MoDE) algorithm for the optimal operation of a complex multipurpose reservoir system. The developed algorithm (MoDE) is compared with the Genetic Algorithm (NSGA-II) using a set of common test problems and the case study. The case study includes part of a complex water supply system located in southwest Brazil that provides water for approximately 20 million people in the Sao Paulo metropolitan area (SPMA). The objectives of the case study include minimization of demand shortage (the difference between demand for water and available water supply), maximization of water quality (or minimization of the deviation from the water quality standards), and minimization of pumping cost. MoDE is applied to the case study using two inflow scenarios: (1) a drought period with inflows below historical average; and (2) a wet period with inflows above historical average. Multiobjective analysis is done by comparing two pairs of objective functions: minimization of demand shortage versus minimization of pumping cost and minimization of demand shortage versus minimization of the deviation from water quality standards. The constraints for the analysis are reservoir capacity, tunnels and channel limitations, and minimum downstream flow for all reservoirs. The proposed MoDE algorithm is outperforming NSGA-II as it converges closer to and provides better spread coverage of the true Pareto front.
ISSN:0887-3801
1943-5487
DOI:10.1061/(ASCE)CP.1943-5487.0000213